WO2022110043A1 - Procédé et appareil de détection d'érosion, et support lisible par ordinateur - Google Patents

Procédé et appareil de détection d'érosion, et support lisible par ordinateur Download PDF

Info

Publication number
WO2022110043A1
WO2022110043A1 PCT/CN2020/132353 CN2020132353W WO2022110043A1 WO 2022110043 A1 WO2022110043 A1 WO 2022110043A1 CN 2020132353 W CN2020132353 W CN 2020132353W WO 2022110043 A1 WO2022110043 A1 WO 2022110043A1
Authority
WO
WIPO (PCT)
Prior art keywords
target
component
depth value
detected
erosion
Prior art date
Application number
PCT/CN2020/132353
Other languages
English (en)
Chinese (zh)
Inventor
董晓滨
赵杰
许晓东
Original Assignee
西门子股份公司
西门子（中国）有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 西门子股份公司, 西门子（中国）有限公司 filed Critical 西门子股份公司
Priority to PCT/CN2020/132353 priority Critical patent/WO2022110043A1/fr
Publication of WO2022110043A1 publication Critical patent/WO2022110043A1/fr

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis

Definitions

  • the present invention relates to the technical field of non-destructive testing, and in particular, to an erosion detection method, device and computer-readable medium.
  • Ceramic heat shield is located on the outer layer of the thermal protection structure on the inner surface of the gas turbine and has excellent ablation resistance. Defects such as damage and falling blocks, when the ceramic insulation tile has defects such as cracks, damage and falling blocks, the high temperature will cause damage to the metal casing of the combustion chamber. Therefore, the erosion detection of ceramic insulation tiles is an important link in the routine inspection process of gas turbines. According to the results of erosion detection, it can be determined whether the ceramic insulation tiles need to be replaced.
  • the erosion detection method, device and computer readable medium provided by the present invention can improve the efficiency of erosion detection.
  • an embodiment of the present invention provides an erosion detection method, including:
  • the depth values of at least two target points on the component to be detected are determined, wherein the depth value of any target point on the component to be detected is used to represent The distance between the target point and the center point of the two lenses included in the binocular camera;
  • the degree of erosion of the component to be inspected is determined.
  • an embodiment of the present invention further provides an erosion detection device, including:
  • an acquisition module configured to acquire a first detection image and a second detection image of the component to be detected, wherein the first detection image and the second detection image are respectively collected by two cameras included in the binocular camera;
  • An image processing module for determining at least two target points on the component to be detected according to the parallax of the first detection image acquired by the acquisition module and the second detection image acquired by the acquisition module , wherein the depth value of any target point on the component to be detected is used to represent the distance between the target point and the center point of the two lenses included in the binocular camera;
  • An erosion judging module is used for determining the degree of erosion of the part to be inspected according to the depth value of each of the target points on the part to be inspected determined by the image processing module.
  • an embodiment of the present invention further provides another erosion detection apparatus, including: at least one memory and at least one processor;
  • the at least one memory for storing a machine-readable program
  • the at least one processor is configured to invoke the machine-readable program to execute the method provided in the first aspect.
  • an embodiment of the present invention further provides a computer-readable medium, where computer instructions are stored on the computer-readable medium, and when executed by a processor, the computer instructions cause the processor to execute the above-mentioned first method provided by the aspect.
  • the first detection image and the second detection image of the component to be detected respectively collected by the two cameras included in the binocular camera are acquired, according to the first detection image and the second detection image. 2. Detect the parallax of the image, determine the depth value of at least two target points on the component to be detected, and then determine the degree of erosion of the component to be detected according to the depth value of each target point, wherein the depth value of any target point on each component to be detected It is used to characterize the distance between the target point and the center point of the two lenses included in the binocular camera.
  • the distance between each target point on the component to be detected and the line connecting the center points of the two lenses of the binocular camera can be obtained by using the parallax between the two images captured by the binocular camera.
  • the depth value of each target point can determine the degree of corrosion of the component to be tested, so that the degree of corrosion can be indirectly reflected by the depth value, without the need for staff to perform visual inspection one by one, and then rely on work experience to determine whether the component to be tested needs to be replaced. Thereby, the efficiency of performing erosion detection is improved.
  • the depth value of each target point on the component to be detected according to the parallax of the first detection image and the second detection image it is possible to first determine that the target point is in pixel points corresponding to the first detection image and the second detection image, and then determine the parallax of the first detection image and the second detection image to determine the depth value of the target point.
  • the depth value can be determined in the following ways:
  • the target parallax is used to represent the relative position of the first pixel point in the first detection image and the second pixel point The difference between the relative positions of the pixel points in the second detection image;
  • the depth value of the target point is determined according to the target parallax, the focal length of the camera in the binocular camera, and the distance between the optical centers of the two cameras in the binocular camera.
  • the depth value is the distance from the target point on the component to be detected to the plane of the binocular camera, it can indirectly reflect the erosion information on the upper surface of the component to be detected, and then can treat Test components for objective and reasonable evaluation. At the same time, there is no need for staff to perform visual inspection based on experience, thereby further improving the efficiency of erosion inspection.
  • the corrosion degree of the component to be tested can be determined by the following methods:
  • the depth value of each of the target points on the edge of the component to be detected is within the preset threshold range, determine the depth of the component to be detected according to the depth value of each of the target points on the component to be detected degree of erosion;
  • the degree of erosion of the part to be inspected is determined according to the calibrated depth value of each of the target points on the part to be inspected.
  • the depth value of each target point located at the edge of the component to be detected is within a preset threshold range, it can be determined whether there is an included angle between the imaging plane of the binocular camera and the surface of the component to be detected, If the depth value of each target point located at the edge of the part to be inspected is within the preset threshold range, then there is no included angle (ie parallel) between the imaging plane of the binocular camera and the surface of the part to be inspected, and the determined The depth value of the target point determines the degree of erosion of the component to be detected; if the depth values of each target point located on the edge of the component to be detected are not all within the preset threshold range, it needs to be determined according to the depth value of each target point on the edge of the component to be detected.
  • the angle between the imaging plane of the binocular camera and the surface of the part to be inspected (that is, not parallel), and the depth value of each target point on the part to be inspected is calibrated according to the angle, and then according to the depth value of each target after calibration
  • the effective detection of the component to be detected may be determined first. area, and then determine the erosion degree of the component to be inspected according to the depth value of each target point in the effective inspection area.
  • the corrosion degree of the component to be tested can be determined by the following methods:
  • an effective detection area on the component to be detected is determined, wherein the effective detection area includes at least two the target point, and the depth value of each of the target points in the effective detection area is within the set range;
  • the degree of erosion of the component to be detected is determined.
  • the effective detection area is determined according to the depth value of each target point and the distribution of each target point on the component to be detected, so that the target points far away from the center of the component to be detected, with a small number and a large error can be removed, Only the area where 90% of the target points concentrated on the parts to be inspected are reserved as the effective detection area, so as to determine the degree of erosion of the parts to be inspected according to the depth value of each target point in the effective inspection area, so as to realize the detection of each target point. Noise reduction processing of depth values further improves the accuracy and reliability of erosion detection.
  • the maximum depth of The difference between the value and the minimum depth value further determines the degree of erosion of the component to be inspected.
  • the corrosion degree of the component to be tested can be determined by the following methods:
  • first target depth value is the maximum value among the depth values of each of the target points on the component to be detected
  • second target depth value is the minimum value among the depth values of each of the target points on the component to be detected
  • the component to be inspected has an erosion degree that needs to be replaced.
  • the maximum depth value and the minimum depth value are respectively determined from the depth values of each target point on the component to be detected, and the target difference value is compared by calculating the target difference value between the maximum depth value and the minimum depth value.
  • the preset threshold if the target difference is not greater than the preset threshold, it is determined that the component to be detected is an erosion degree that does not need to be replaced temporarily; if the target difference is greater than the preset threshold, it is determined that the component to be detected is The level of erosion that needs to be replaced.
  • the target difference is the actual maximum erosion depth of the surface of the component to be detected. Therefore, when the target difference exceeds the set standard value (ie, the preset threshold), the component to be detected needs to be replaced. Detection of corrosion levels of components. This process eliminates the need for personnel to perform visual inspections with experience, increasing the efficiency of erosion inspections.
  • FIG. 2 is a flowchart of a method for acquiring a depth value provided by an embodiment of the present invention
  • FIG. 3 is a flowchart of a method for determining an erosion degree provided by an embodiment of the present invention.
  • FIG. 4 is a flowchart of another method for determining the degree of erosion provided by an embodiment of the present invention.
  • FIG. 5 is a flowchart of another method for determining an erosion degree provided by an embodiment of the present invention.
  • FIG. 6 is a flowchart of another erosion detection method provided by an embodiment of the present invention.
  • FIG. 7 is a schematic diagram of an erosion detection device provided by an embodiment of the present invention.
  • FIG. 8 is a schematic diagram of another erosion detection device provided by an embodiment of the present invention.
  • FIG. 9 is a schematic diagram of another erosion detection device provided by an embodiment of the present invention.
  • FIG. 10 is a schematic diagram of still another erosion detection device provided by an embodiment of the present invention.
  • FIG. 11 is a schematic diagram of still another erosion detection device provided by an embodiment of the present invention.
  • FIG. 12 is a schematic diagram of an erosion detection apparatus including a memory and a processor provided by an embodiment of the present invention.
  • Memory 705 Processor 7021: Pixel acquisition unit
  • the first relationship determination unit 7033 The second relationship determination unit 7034: The area determination unit
  • Second erosion determination unit 7036 Depth value filtering unit 7037: Operation unit
  • the second judgment unit 7039 The erosion degree determination unit
  • the staff in the current corrosion detection of ceramic thermal insulation tiles in gas turbines, the staff usually enters the combustion chamber through the manhole, and directly visually inspects them with the naked eye, and determines the position, direction and length of the cracks against the ceramic defect template. Etc., based on work experience to determine the crack depth of the ceramic thermal insulation tile, and then determine the ceramic thermal insulation tile that needs to be replaced. This method is labor-intensive, slow in detection and susceptible to subjective factors, resulting in low efficiency in corrosion detection of ceramic insulation tiles.
  • the first detection image and the second detection image of the component to be detected respectively collected by the two cameras included in the binocular camera are acquired, and according to the target points corresponding to the first detection image and the second detection image, respectively According to the coordinate difference between the two pixel points, the target parallax of the target point in the first detection image and the second detection image is determined, and according to the target parallax, the distance between the optical centers of the two cameras in the binocular camera The distance between and the focal length of the camera determine the depth value of the target point. In this way, the depth value of each target point in the component to be detected can be obtained, and the maximum depth value and the minimum depth value are respectively determined from the depth values of each target point.
  • the threshold value When the target difference between the maximum depth value and the minimum depth value is greater than the preset value When the threshold value is reached, it can be determined that the component to be detected is the degree of corrosion that needs to be replaced, so as to realize the detection of the degree of corrosion of the component to be detected. This process eliminates the need for personnel to perform visual inspections with experience, increasing the efficiency of erosion inspections.
  • the first detection image and the second detection image may also be collected by two cameras of the binocular camera, the two cameras in the binocular camera have the same focal length, and the two cameras in the binocular camera have the same focal length.
  • the depth value of any target point on the component to be detected is used to represent the distance between the target point and the center point of the two lenses included in the binocular camera.
  • the target parallax is used to represent the difference between the relative position of the first pixel point in the first detection image and the relative position of the second pixel point in the second detection image.
  • an embodiment of the present invention provides an erosion detection method, and the method may include the following steps:
  • Step 101 Acquire a first detection image and a second detection image of the component to be detected, wherein the first detection image and the second detection image are respectively collected by two cameras included in the binocular camera;
  • Step 102 Determine the depth values of at least two target points on the component to be detected according to the parallax of the first detection image and the second detection image, wherein the depth value of any target point on the component to be detected is used to characterize the target point and the dual target point.
  • Step 103 Determine the degree of erosion of the component to be detected according to the depth values of each target point on the component to be detected.
  • the first detection image and the second detection image of the component to be detected that are respectively collected by two cameras included in the binocular camera are acquired, and the to-be-detected image is determined according to the parallax of the first detection image and the second detection image.
  • the depth values of at least two target points on the component and then determine the degree of erosion of the component to be detected according to the depth value of each target point, wherein the depth value of any target point on each component to be detected is used to characterize the target point and the The distance between the center points of the two lenses included in the binocular camera.
  • the distance between each target point on the component to be detected and the line connecting the center points of the two lenses of the binocular camera can be obtained by using the parallax between the two images captured by the binocular camera.
  • the depth value of each target point can determine the degree of corrosion of the component to be tested, so that the degree of corrosion can be indirectly reflected by the depth value, without the need for staff to perform visual inspection one by one, and then rely on work experience to determine whether the component to be tested needs to be replaced. Non-destructive testing of components to be tested is achieved, thereby improving the efficiency of corrosion testing.
  • the left and right cameras included in the binocular camera simultaneously capture images of the component to be detected, wherein the distance from the binocular camera to the surface of the component to be detected can be determined according to user requirements.
  • the distance from the binocular camera to the surface of the part to be inspected can be adjusted according to the size of the part to be inspected. For example, if the size of the ceramic thermal insulation tile inside the gas turbine generator is 20cm*20cm, the distance between the binocular camera plane and the ceramic thermal insulation tile is 30-50cm.
  • the detection image includes multiple components to be detected, the distance from the binocular camera to the surface of the components to be detected can be adjusted according to the number of components to be detected.
  • the two lenses included in the binocular camera should be placed directly above the surface to be inspected when collecting inspection images.
  • Auxiliary lighting can be used to maintain a good background light source to obtain inspection images with clear image quality, thereby improving the accuracy of erosion detection. and reliability.
  • the present invention there is a deviation between the positions of the pixels imaged by the two cameras in the same scene, that is, parallax.
  • parallax Based on the parallax, according to the relative positional relationship between the left and right cameras and the parameter information of the camera itself, the spatial distribution of the target can be obtained.
  • Depth information which is used to represent the distance of a certain point on the target in the scene from the camera. Therefore, by means of the parallax of the first detection image and the second detection image collected by the binocular camera, the depth value of the target point of the component to be detected can be determined.
  • the three-dimensional position information of the target in space can be obtained according to the depth value information. Therefore, according to the depth value of each target point on the part to be inspected, the three-dimensional position information of the part to be inspected in space can be determined, and then the three-dimensional position information of the part to be inspected can be determined. The degree of corrosion of the parts, to achieve non-destructive testing of the parts to be tested.
  • determining the depth value of each target point on the component to be detected according to the parallax of the first detection image and the second detection image it can be determined that the target point is in the first detection image.
  • the pixel points corresponding to the first detection image and the second detection image are further determined to determine the parallax of the first detection image and the second detection image to determine the depth value of the target point.
  • determining the depth value according to the disparity can be implemented as follows:
  • Step 201 for each target point on the component to be detected, determine the first pixel point corresponding to the target point in the first detection image, and determine the second pixel point corresponding to the target point in the second detection image;
  • Step 202 Determine the target parallax between the first pixel point and the second pixel point, wherein the target parallax is used to represent the relative position of the first pixel point in the first detection image and the position of the second pixel point in the second detection image. difference in relative position;
  • Step 203 Determine the depth value of the target point according to the target parallax, the focal length of the camera in the binocular camera, and the distance between the optical centers of the two cameras in the binocular camera.
  • the corresponding pixel points of the target point in the first detection image and the second detection image are determined, and according to the coordinates of the pixel point, it is determined that the target point is in the first detection image and the second detection image.
  • the difference between the relative positions of the two detection images is the target parallax of the target point, and then the depth of the target point is obtained through parameters such as the target parallax, the focal length of the camera in the binocular camera, and the distance between the optical centers of the two cameras. value.
  • the first detection image may be used as a reference, and for each target point, the pixel coordinates of the first pixel point corresponding to the target point in the reference image may be used as a template, and the second detection image may be searched for the For the same or similar target points, the pixel coordinates of the second pixel point are determined, and the disparity is determined by the positional deviation between the pixel coordinates of the two pixel points. Because the binocular cameras are usually placed horizontally, the positional deviation is generally reflected in the horizontal direction.
  • the coordinate of point X in the scene in the horizontal direction of the left camera is x
  • the coordinate of the image in the horizontal direction of the right camera is x+p
  • p is the parallax of point X.
  • a parallax map of the image to be detected can be obtained.
  • the parallax map can be based on the first detected image, its size is the size of the first detected image, and the element value is the parallax of each target point. , so that the disparity of each target point can be intuitively obtained through the disparity map, which is convenient for subsequent acquisition of the depth value of each target point.
  • the depth value of each target point is determined by the following formula:
  • h is used to characterize the depth value of each target point in the part to be detected
  • b is used to characterize the distance between the optical centers of the two cameras in the binocular camera
  • c is used to characterize the focal length of the camera in the binocular camera
  • p is used to characterize The parallax of each target point between the first detection image and the second detection image is characterized.
  • the depth value is used to represent the distance between the target point and the center point of the two lenses included in the binocular camera, because the erosion information on the upper surface of the component to be detected can be reflected by the depth value, thereby enabling The objective and reasonable evaluation of the parts to be tested is carried out, the non-destructive testing of the parts to be tested is realized, and the visual inspection is avoided, thereby further improving the efficiency of corrosion testing.
  • determining the degree of erosion of the component to be detected according to the depth value of each target point on the component to be detected you can first determine the degree of erosion of the component to be detected according to the depth of each target point on the edge of the component to be detected.
  • the depth value ensures that the surface of the part to be inspected is parallel to the imaging plane of the binocular camera, thereby determining the degree of erosion of the part to be inspected.
  • determining the degree of erosion of the component to be inspected can be achieved as follows:
  • Step 301 determine whether the depth value of each target point located at the edge of the component to be detected is within the preset threshold range, if it is Y, go to step 302, if not N, go to step 303;
  • Step 302 According to the depth value of each target point on the component to be detected, determine the degree of erosion of the component to be detected, and end the current process;
  • Step 303 Determine the angle between the imaging plane of the binocular camera and the surface of the component to be detected according to the depth value of each target point on the edge of the component to be detected;
  • Step 304 Calibrate the depth value of each target point on the component to be detected according to the included angle
  • Step 305 Determine the degree of erosion of the component to be detected according to the calibrated depth values of each target point on the component to be detected, and end the current process.
  • the depth value of each target point located at the edge of the component to be detected is within a preset threshold range, it can be determined whether there is an included angle between the imaging plane of the binocular camera and the surface of the component to be detected, If the depth value of each target point located at the edge of the component to be detected is within the preset threshold range, then there is no included angle (that is, parallel) between the imaging plane of the binocular camera and the surface of the component to be detected, and the determined
  • the depth value of the target point determines the degree of erosion of the component to be detected; if the depth values of each target point located on the edge of the component to be detected are not all within the preset threshold range, it needs to be determined according to the depth value of each target point on the edge of the component to be detected.
  • the angle between the imaging plane of the binocular camera and the surface of the part to be inspected (that is, not parallel), and the depth value of each target point on the part to be inspected is calibrated according to the angle, and then according to the depth value of each target after calibration
  • the depth value of each target point located at the edge of the component to be detected is within the preset threshold range.
  • the threshold range is set to 50cm ⁇ 0.5cm. If the depth values of each target point on the edge of the component to be detected are 49.5cm, 49.6cm, 50.3cm, 49.8cm, 49.5cm, 50cm, 49.7cm, 50.1cm and 50.5cm respectively, the It is determined that the depth values of each target point are all within the preset threshold range, that is, the imaging plane of the binocular camera is parallel to the surface of the component to be detected.
  • the depth value of each target point in the component to be detected can be calibrated in the following manner:
  • S1 Determine the minimum depth value (A) and the maximum depth value (B) from the depth values of each target point on the edge of the component to be detected;
  • h i is used to represent the depth value of the i target point in the component to be detected after calibration processing
  • ⁇ is used to represent the angle between the imaging plane of the binocular camera and the surface of the component to be detected
  • h b is used to represent the maximum
  • the depth value (B) ha is used to represent the minimum depth value (A)
  • x b is used to represent the abscissa of the pixel corresponding to the B target point corresponding to the maximum depth value (B) in the first detection image
  • x a is used to represent the abscissa of the pixel point corresponding to the A target point corresponding to the minimum depth value (A) in the first detection image
  • h i 1 is used to represent the i target point in the component to be detected before the calibration process.
  • Depth value; x i is used to represent the abscissa of the pixel point corresponding to the i target point in the first detection image.
  • the component to be detected may be other components in the gas turbine, such as a blade, but the surface of the blade is an arc surface. Therefore, during the erosion detection process, it is necessary to use the above-mentioned depth value of each target point in the component to be detected for calibration way to calibrate the depth value of the blade.
  • the effective detection area of the component to be detected can be determined first, and then The erosion degree of the component to be inspected is determined according to the depth value of each target point in the effective inspection area.
  • determining the degree of erosion of the component to be inspected can be achieved in the following ways:
  • Step 401 According to the depth value of each target point and the distribution of each target point on the component to be detected, determine the effective detection area on the component to be detected, wherein, the effective detection area includes at least two target points, and the effective detection area The depth value of each target point is within the set range;
  • Step 402 Determine the degree of erosion of the component to be detected according to the depth value of each target point in the effective detection area.
  • the effective detection area is determined according to the depth value of each target point and the distribution of each target point on the component to be detected, so that the target points far away from the center of the component to be detected, with a small number and a large error can be removed, Only the area where 90% of the target points concentrated on the parts to be inspected are reserved as the effective detection area, so as to determine the degree of erosion of the parts to be inspected according to the depth value of each target point in the effective inspection area, so as to realize the detection of each target point.
  • the noise reduction processing of depth value further improves the accuracy and reliability of erosion detection.
  • a polymorphic filter may be used to remove abnormal depth values, so as to realize noise reduction processing on the depth values of each target point and reduce errors in the erosion detection result.
  • the degree of erosion of the component to be inspected may be further determined by the difference between the maximum depth value and the minimum depth value.
  • the method for determining the degree of erosion of the component to be inspected includes the following steps:
  • Step 501 Determine a first target depth value and a second target depth value, wherein the first target depth value is the maximum value among the depth values of each target point on the component to be detected, and the second target depth value is the depth value of each target point on the component to be detected. The minimum value among the depth values of the target point;
  • Step 502 Perform a difference operation on the first target depth value and the second target depth value to obtain a target difference value
  • Step 503 Determine whether the absolute value of the target difference is greater than the preset threshold, if it is Y, go to step 504, if not N, go to step 505;
  • Step 504 Determine the corrosion degree of the component to be detected that needs to be replaced, and end the current process
  • Step 505 Determine the corrosion degree of the component to be inspected that does not need to be replaced, and end the current process.
  • the maximum depth value and the minimum depth value are respectively determined from the depth values of each target point on the component to be detected, and the target difference value is compared by calculating the target difference value between the maximum depth value and the minimum depth value.
  • the preset threshold if the target difference is not greater than the preset threshold, it is determined that the component to be detected is an erosion degree that does not need to be replaced temporarily; if the target difference is greater than the preset threshold, it is determined that the component to be detected is The level of erosion that needs to be replaced.
  • the target difference is the actual maximum erosion depth of the surface of the component to be detected. Therefore, when the target difference exceeds the set standard value (ie, the preset threshold), the component to be detected needs to be replaced. Detection of corrosion levels of components. This process eliminates the need for personnel to perform visual inspections with experience, increasing the efficiency of erosion inspections.
  • the target difference between the maximum depth value and the minimum depth value among the depth values of each target point on the component to be detected is greater than a preset threshold, it is determined that the component to be detected is an erosion degree that needs to be replaced , and output the target difference, which is the actual erosion depth. Based on all the output target difference values and the parts to be inspected, an inspection report for this inspection can also be automatically generated.
  • the inspection report can include the location of the inspected parts that need to be replaced, the erosion condition, the erosion depth value, and the maintenance date. and other statistical data, thereby helping to complete the erosion detection work faster and improve the efficiency of erosion detection.
  • a parallax map of the image to be detected can be obtained, and the depth value of each target point on the component to be detected is converted to the parallax map to obtain a depth map, a depth map It can be a grayscale image or a pseudo-color image, but the pixel value of the depth map is the actual distance between the target point and the center point of the two lenses included in the binocular camera.
  • the color in the depth map represents the depth.
  • a three-dimensional image corresponding to the part to be inspected can be obtained according to the depth map, wherein the three-dimensional image includes the three-dimensional position information and depth value of each target point of the part to be inspected in space, and the three-dimensional image of the part to be inspected can be visually seen through the three-dimensional image.
  • the topography information is more visualized, and it is convenient to directly judge the two-dimensional topography and erosion depth of the surface of the component to be tested.
  • the method may include the following steps:
  • Step 601 Acquire a first inspection image and a second inspection image of the component to be inspected.
  • the first detection image and the second detection image may be collected by two cameras of the binocular camera or two cameras in the binocular camera, and the first detection image and the second detection image may include a to-be-detected image.
  • the image of the inspection part may also include images of a plurality of parts to be inspected.
  • a binocular camera is used, and the binocular camera is placed on the surface of the ceramic thermal insulation tile to be detected at a position where the distance between the binocular camera plane and the ceramic thermal insulation tile is 50cm.
  • auxiliary lighting a first inspection image and a second inspection image of the ceramic thermal insulation tile are collected.
  • Step 602 Determine the target disparity of the target point.
  • each target point on the component to be detected determines the first pixel point and the second pixel point corresponding to the target point in the first detection image and the second detection image respectively, and according to the The difference between the relative positions of one pixel point and the second pixel point determines the target parallax of the target point in the first detection image and the second detection image.
  • the first pixel point X1 (x1, y1) corresponding to the X point in the first detection image, and determine the first pixel point X1 (x1, y1) in the second detection image.
  • the corresponding second pixel point X2 (x2, y2), according to the difference in the relative position of X1 and X2 in the horizontal direction, determine the target parallax of point X in the first detection image and the second detection image is x1-x2 absolute. value.
  • Step 603 Determine the depth value of the target point.
  • the depth value of each target point is determined by the following formula:
  • h is used to characterize the depth value of each target point in the part to be detected
  • b is used to characterize the distance between the optical centers of the two cameras in the binocular camera
  • c is used to characterize the focal length of the camera in the binocular camera
  • p is used to characterize The parallax of each target point between the first detection image and the second detection image is characterized.
  • the target parallax p is the absolute value of x1-x2
  • the distance between the optical centers of the two cameras in the binocular camera is b
  • the camera in the binocular camera is the absolute value of x1-x2.
  • the focal length is c
  • the depth value h of point X is calculated by the above formula.
  • Step 604 Determine the effective inspection area on the component to be inspected.
  • the effective detection area on the component to be detected is determined according to the depth value of each target point and the distribution of each target point on the component to be detected,
  • the noise reduction processing for the depth value of each target point is realized, wherein at least two target points are included in the effective detection area, and the depth value of each target point in the effective detection area is within the set range.
  • the target points far away from the center of the component to be detected with a small number and a large error can be removed, and only Retain the area where 90% of the target points concentrated on the ceramic heat insulation tile are located as the effective detection area.
  • Step 605 Determine whether the depth value of each target point on the edge of the component to be detected is within the preset threshold range, if yes, go to Step 607, if not, go to Step 606.
  • step 607 is performed for the depth value of each target point on the component to be detected, if the depth value of each target point on the edge is not within the preset threshold value range, then for the component to be detected.
  • Step 606 is performed on the depth value of each upper target point.
  • step 606 determines whether the depth value of each target point located on the inner edge of the effective detection area is within 50cm ⁇ 0.5cm, if the depth of each target point on the edge is within 50cm ⁇ 0.5cm
  • the values are 49.5cm, 60cm, 56.8cm, 54.2cm, 52.5cm, 50cm, 49.7cm, 53.1cm and 56.2cm respectively, then the depth value of each target point on the edge is not within the preset threshold range, and the imaging of the binocular camera If the plane is not parallel to the surface of the component to be inspected, step 606 is executed.
  • Step 606 Calibrate the depth value of each target point on the component to be detected.
  • the angle between the imaging plane of the binocular camera and the surface of the component to be detected is determined according to the depth value of each target point on the edge of the component to be detected, and the depth value of each target point on the edge of the component to be detected is determined from the depth value of each target point on the edge of the component to be detected. Determine the minimum depth value (A) and the maximum depth value (B) respectively;
  • the depth value of each target point in the component to be detected is calibrated by the following formula:
  • h i is used to represent the depth value of the i target point in the component to be detected after calibration processing
  • ⁇ is used to represent the angle between the imaging plane of the binocular camera and the surface of the component to be detected
  • h b is used to represent the maximum
  • the depth value (B) ha is used to represent the minimum depth value (A)
  • x b is used to represent the abscissa of the pixel corresponding to the B target point corresponding to the maximum depth value (B) in the first detection image
  • x a is used to represent the abscissa of the pixel point corresponding to the A target point corresponding to the minimum depth value (A) in the first detection image
  • h i 1 is used to represent the i target point in the component to be detected before the calibration process.
  • Depth value; x i is used to represent the abscissa of the pixel point corresponding to the i target point in the first detection image.
  • the minimum depth value (A: 50cm) and the maximum depth value (B: 60cm) are respectively determined from the depth values of each target point on the edge of the component to be detected, and the corresponding point A in the first detection image is determined.
  • the pixel coordinates (1, 2) are determined, the pixel coordinates (19, 4) corresponding to point B in the first detection image are determined, and the distance between the imaging plane of the binocular camera and the surface of the component to be detected is determined by the above formula.
  • the angle is arctan5/9
  • the Y point on the ceramic heat insulation tile the pixel coordinate in the first detection image is (10,9)
  • its depth value is 60cm
  • the calibration is performed by the above formula to obtain the calibration
  • the depth value of the rear Y point is 55cm (ie 60-5).
  • Step 607 Determine the first target depth value and the second target depth value.
  • a first target depth value and a second target depth value are determined, wherein the first target depth value is the maximum value among the depth values of each target point on the component to be detected, and the second target depth value is the value to be detected. Detects the minimum value of the depth values of each target point on the part.
  • the maximum depth value is Y 55cm
  • the minimum depth value is 50cm
  • Step 608 Perform a difference operation on the first target depth value and the second target depth value.
  • a difference value operation is performed on the first target depth value and the second target depth value to obtain a target difference value.
  • the maximum depth value is Y 55cm
  • the minimum depth value is 50cm
  • the target difference is 5cm.
  • Step 609 Determine the erosion degree of the component to be inspected.
  • the component to be inspected when judging whether the absolute value of the target difference is greater than a preset threshold, if so, it is determined that the component to be inspected is an erosion degree that needs to be replaced; if not, it is determined that the component to be inspected is an erosion that does not require replacement. degree.
  • the ceramic thermal insulation tile is the degree of erosion that needs to be replaced.
  • an embodiment of the present invention provides an erosion detection device, including:
  • An acquisition module 701 configured to acquire the first detection image and the second detection image of the component to be detected, wherein the first detection image and the second detection image are respectively collected by two cameras included in the binocular camera;
  • An image processing module 702 for determining the depth values of at least two target points on the component to be detected according to the parallax of the first detection image acquired by the acquisition module 701 and the second detection image acquired by the acquisition module, wherein the The depth value of any target point on the component is used to represent the distance between the target point and the center point of the two lenses included in the binocular camera;
  • An erosion judging module 703 is configured to determine the degree of erosion of the part to be inspected according to the depth values of each target point on the part to be inspected determined by the image processing module 702 .
  • the acquisition module 701 can be used to perform step 101 in the above method embodiments
  • the image processing module 702 can be used to perform step 102 in the above method embodiments
  • the erosion determination module 703 can be used to perform the above method embodiments. step 103.
  • the image processing module 702 includes:
  • a pixel point acquisition unit 7021 for each target point on the component to be detected, to determine the first pixel point corresponding to the target point in the first detection image, and to determine the target point corresponding to the second detection image.
  • a depth value acquisition unit 7023 configured to determine the depth value of the target point according to the focal length of the camera in the binocular camera, the distance between the optical centers of the two cameras in the binocular camera, and the target parallax determined by the parallax acquisition unit 7022.
  • the pixel point acquisition unit 7021 may be used to perform step 201 in the above method embodiments
  • the parallax acquisition unit 7022 may be used to perform step 202 in the above method embodiments
  • the depth value acquisition unit 7023 may be used to perform the above mentioned method embodiments. Step 203 in the method embodiment.
  • the erosion judgment module 703 includes:
  • a first judgment unit 7031 for judging whether the depth value of each target point located at the edge of the component to be detected is within the preset threshold range
  • a first relationship determination unit 7032 is used for when the first judgment unit 7031 determines that the depth value of each target point on the edge of the component to be detected is within the preset threshold range, then according to the depth value of each target point on the component to be detected, Determine the degree of erosion of the part to be inspected;
  • a second relationship determination unit 7033 is used for when the first judgment unit 7031 determines that the depth values of each target point on the edge of the component to be detected are not all within the preset threshold range, according to the depth of each target point on the edge of the component to be detected.
  • the value determines the angle between the imaging plane of the binocular camera and the surface of the part to be inspected, and calibrates the depth value of each target point on the part to be inspected according to the angle, and according to the calibrated depth value of each target point on the part to be inspected The depth value determines the degree of erosion of the part to be inspected.
  • the first judging unit 7031 may be configured to perform step 301 in the foregoing method embodiments
  • the first relationship determining unit 7032 may be configured to execute step 302 in the foregoing method embodiments
  • the second relationship determining unit 7033 may be configured to perform Steps 304 and 305 in the above method embodiments are performed.
  • the erosion judgment module 703 includes:
  • An area determination unit 7034 for determining the effective detection area on the component to be detected according to the depth value of each target point and the distribution of each target point on the component to be detected, wherein the effective detection area includes at least two target points , and the depth value of each target point in the effective detection area is within the set range;
  • a second erosion determination unit 7035 is configured to determine the degree of erosion of the component to be inspected according to the depth values of each target point in the effective inspection area determined by the area determination unit 7034 .
  • the region determination unit 7034 may be configured to perform step 401 in the above method embodiments, and the second erosion determination unit 7035 may be configured to perform step 402 in the above method embodiments.
  • the erosion determination module 703 includes:
  • a depth value screening unit 7036 for determining a first target depth value and a second target depth value, wherein the first target depth value is the maximum value among the depth values of each target point on the component to be detected, and the second target depth value is is the minimum value among the depth values of each target point on the component to be detected;
  • An erosion degree determination unit 7039 configured to determine that the component to be detected is an erosion degree that needs to be replaced when the absolute value of the target difference determined by the second determination unit 7038 is greater than a preset threshold.
  • the depth value screening unit 7036 may be configured to perform step 501 in the foregoing method embodiments
  • the computing unit 7037 may be configured to perform step 502 in the foregoing method embodiments
  • the second determining unit 7038 may be configured to execute the foregoing method implementations
  • the erosion degree determination unit 7039 may be used to perform steps 504 and 505 in the above method embodiments.
  • an embodiment of the present invention provides an erosion detection apparatus, including: at least one memory 704 and at least one processor 705;
  • the at least one memory 704 for storing a machine-readable program
  • the at least one processor 705 is configured to invoke the machine-readable program to execute the erosion detection methods provided in the foregoing embodiments.
  • the present invention also provides a computer-readable medium storing instructions for causing a machine to perform the erosion detection method as described herein.
  • a system or device equipped with a storage medium on which software program codes for implementing the functions of any of the above-described embodiments are stored, and which enables a computer (or CPU or MPU of the system or device) ) to read and execute the program code stored in the storage medium.
  • the program code itself read from the storage medium can implement the functions of any of the above-described embodiments, and thus the program code and the storage medium storing the program code form part of the present invention.
  • Examples of storage media for providing program code include floppy disks, hard disks, magneto-optical disks, optical disks (eg CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), Magnetic tapes, non-volatile memory cards and ROMs.
  • the program code may be downloaded from a server computer over a communications network.
  • the program code read from the storage medium is written into the memory provided in the expansion board inserted into the computer or into the memory provided in the expansion module connected with the computer, and then based on the program code
  • the instructions cause the CPU or the like installed on the expansion board or expansion module to perform part and all of the actual operations, so as to realize the functions of any one of the above-mentioned embodiments.
  • the hardware modules may be implemented mechanically or electrically.
  • a hardware module may include permanent dedicated circuits or logic (eg, dedicated processors, FPGAs or ASICs) to perform corresponding operations.
  • the hardware modules may also include programmable logic or circuits (eg, general-purpose processors or other programmable processors), which may be temporarily set by software to complete corresponding operations.
  • the specific implementation mechanical, or dedicated permanent circuit, or temporarily provided circuit can be determined based on cost and time considerations.

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Length Measuring Devices By Optical Means (AREA)

Abstract

L'invention concerne un procédé et un appareil de détection d'érosion, ainsi qu'un support lisible par ordinateur. Le procédé de détection d'érosion comprend les étapes consistant à acquérir une première image de détection et une seconde image de détection d'un composant à détecter (101), la première image de détection et la seconde image de détection étant respectivement collectées par deux caméras qui sont comprises dans une caméra binoculaire ; à déterminer des valeurs de profondeur d'au moins deux points cibles sur ledit composant en fonction de la parallaxe de la première image de détection et de la seconde image de détection (102), la valeur de profondeur de tout point cible sur ledit composant étant utilisée pour représenter la distance entre le point cible et une ligne de connexion de points centraux de deux lentilles qui sont comprises dans la caméra binoculaire ; et à déterminer un degré d'érosion dudit composant en fonction de la valeur de profondeur de chaque point cible sur ledit composant (103). Au moyen du procédé, l'efficacité de détection d'érosion peut être améliorée.
PCT/CN2020/132353 2020-11-27 2020-11-27 Procédé et appareil de détection d'érosion, et support lisible par ordinateur WO2022110043A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
PCT/CN2020/132353 WO2022110043A1 (fr) 2020-11-27 2020-11-27 Procédé et appareil de détection d'érosion, et support lisible par ordinateur

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2020/132353 WO2022110043A1 (fr) 2020-11-27 2020-11-27 Procédé et appareil de détection d'érosion, et support lisible par ordinateur

Publications (1)

Publication Number Publication Date
WO2022110043A1 true WO2022110043A1 (fr) 2022-06-02

Family

ID=81753828

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2020/132353 WO2022110043A1 (fr) 2020-11-27 2020-11-27 Procédé et appareil de détection d'érosion, et support lisible par ordinateur

Country Status (1)

Country Link
WO (1) WO2022110043A1 (fr)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115100203A (zh) * 2022-08-25 2022-09-23 山东振鹏建筑钢品科技有限公司 一种钢筋打磨除锈质量检测方法
CN116363136A (zh) * 2023-06-01 2023-06-30 山东创元智能设备制造有限责任公司 一种机动车部件自动化生产在线筛选方法及系统

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20040183900A1 (en) * 2003-03-20 2004-09-23 Everest Vit Method and system for automatically detecting defects in remote video inspection applications
US20100045955A1 (en) * 2008-08-20 2010-02-25 Asml Holding N.V. Particle Detection on an Object Surface
CN107578397A (zh) * 2017-07-25 2018-01-12 西南交通大学 一种新型非接触式接触线磨损检测方法
CN109615654A (zh) * 2019-01-09 2019-04-12 中国矿业大学(北京) 基于双目视觉的排水管道内表面腐蚀深度及面积测量方法
CN110033447A (zh) * 2019-04-12 2019-07-19 东北大学 一种基于点云方法的高铁重轨表面缺陷检测方法
CN110186934A (zh) * 2019-06-12 2019-08-30 中国神华能源股份有限公司 轴箱橡胶垫裂纹检测方法和检测装置
CN110706182A (zh) * 2019-10-10 2020-01-17 普联技术有限公司 一种屏蔽罩平面度检测方法、装置、终端设备及存储介质

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20040183900A1 (en) * 2003-03-20 2004-09-23 Everest Vit Method and system for automatically detecting defects in remote video inspection applications
US20100045955A1 (en) * 2008-08-20 2010-02-25 Asml Holding N.V. Particle Detection on an Object Surface
CN107578397A (zh) * 2017-07-25 2018-01-12 西南交通大学 一种新型非接触式接触线磨损检测方法
CN109615654A (zh) * 2019-01-09 2019-04-12 中国矿业大学(北京) 基于双目视觉的排水管道内表面腐蚀深度及面积测量方法
CN110033447A (zh) * 2019-04-12 2019-07-19 东北大学 一种基于点云方法的高铁重轨表面缺陷检测方法
CN110186934A (zh) * 2019-06-12 2019-08-30 中国神华能源股份有限公司 轴箱橡胶垫裂纹检测方法和检测装置
CN110706182A (zh) * 2019-10-10 2020-01-17 普联技术有限公司 一种屏蔽罩平面度检测方法、装置、终端设备及存储介质

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115100203A (zh) * 2022-08-25 2022-09-23 山东振鹏建筑钢品科技有限公司 一种钢筋打磨除锈质量检测方法
CN115100203B (zh) * 2022-08-25 2022-11-18 山东振鹏建筑钢品科技有限公司 一种钢筋打磨除锈质量检测方法
CN116363136A (zh) * 2023-06-01 2023-06-30 山东创元智能设备制造有限责任公司 一种机动车部件自动化生产在线筛选方法及系统
CN116363136B (zh) * 2023-06-01 2023-08-11 山东创元智能设备制造有限责任公司 一种机动车部件自动化生产在线筛选方法及系统

Similar Documents

Publication Publication Date Title
TWI605249B (zh) 使用無固定形式管理區域之晶圓檢查
JP4707605B2 (ja) 画像検査方法およびその方法を用いた画像検査装置
TWI600897B (zh) 用於偵測晶圓上之缺陷之電腦實施方法、非暫時性電腦可讀媒體及系統
WO2022110043A1 (fr) Procédé et appareil de détection d'érosion, et support lisible par ordinateur
JP2014517265A (ja) タイヤの外面のディジタル画像の分析及び偽測定箇所の処理
WO2015100777A1 (fr) Procédé de détection de défaut et dispositif de détection de défaut de panneau d'affichage
US20150055754A1 (en) X-ray inspection method and x-ray inspection device
CN115731165B (zh) 一种锂电池在线尺寸点检的检测系统及方法
IL262170A (en) A system, method and product A computer program for correcting a change figure is produced from a comparison between a target matrix and a reference matrix
JP2017040600A (ja) 検査方法、検査装置、画像処理装置、プログラム及び記録媒体
TW202238112A (zh) 晶圓表面缺陷檢測方法及其裝置
CN110426395B (zh) 一种太阳能el电池硅片表面检测方法及装置
JP2010181328A (ja) 太陽電池ウェハ表面の検査装置，太陽電池ウェハ表面の検査用プログラム，太陽電池ウェハ表面の検査方法
JP4981433B2 (ja) 検査装置、検査方法、検査プログラムおよび検査システム
JP2002290994A (ja) 小型カメラモジュールの異物検査方法およびその異物検査装置
JP5876139B2 (ja) タイヤの内面のディジタル画像の分析及び偽測定箇所の処理
JP2014016239A (ja) Ｘ線検査方法及びｘ線検査装置
TW201317587A (zh) 尺寸檢測裝置及方法
TWI493177B (zh) 一種檢測具週期性結構光學薄膜的瑕疵檢測方法及其檢測裝置
JP5391172B2 (ja) 異物検査装置及びアライメント調整方法
KR20170035262A (ko) 블레이드 균열 정보 저장방법 및 블레이드 균열 예측방법
JP2003247954A (ja) 円形体周縁部の欠陥検出方法
JP2006284308A (ja) 半導体装置の外観検査方法
JP5870676B2 (ja) 画像処理方法
TWI571829B (zh) 光學檢測方法

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 20962933

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 20962933

Country of ref document: EP

Kind code of ref document: A1